Question 1

Shiny App - Hogwarts Published on shinyapps.io https://zina-kurian.shinyapps.io/hogwartsapp/

library(shiny)

shinyUI(pageWithSidebar(
  headerPanel("Hogwarts Sorting"),
  sidebarPanel(
    h3('Which Hogwarts house should you be in?'),
    textInput(inputId="text1", label = "What is your favorite color?"),
    actionButton("goButton","go")
  ),
  mainPanel(
    h3('Results of sorting...'),
    p('Your color is..'), textOutput('otext1'),
    p("Hmm what house do you think you are? "), textOutput('oresult')
    
      
  )
))

Hogwarts Sorting

Which Hogwarts house should you be in?

Results of sorting...

Your color is..

Hmm what house do you think you are?

##



shinyServer(
  function(input, output) {
    
    output$otext1 = renderPrint({input$text1})
  
    text_reactive <- eventReactive( input$goButton, {
      if (input$text1 == "green") " You're Slytherin"
      else if (input$text1== "purple") " You're Ravenclaw"
      else if (input$text1 == "blue") "You're Hufflepuff"
      else if (input$text1 == "gold") "You're Gryffindor"
      else "Pick a different color...blue,gold,purple,green"
    })
    
    output$oresult = renderPrint({
      text_reactive()
     
    })
  })


##

runApp(‘~/Documents/JHU Grad School/DS4BME/HW4/project/hogwartsapp’, display.mode=“showcase”)

Question 4.2

Recreate plots as ploty interactive, and host them

#library(ggplot2)
datnew = read.table("/Users/zskurian/Documents/JHU Grad School/DS4BME/HW3/classInterests.txt", header=TRUE)
m = ggplot(datnew,aes(x=Year))
m = m + geom_bar()

k = ggplot(datnew,aes(x=Program))
k = k + geom_bar()
ggplotly(k)
library(ggmosaic)
j = ggplot(data = datnew, mapping = aes(x=Program,y=Year))
j = j + geom_mosaic(aes(x=product(Year,Program), fill=Year))
ggplotly(j)
headers3 = read.csv("/Users/zskurian/Documents/JHU Grad School/DS4BME/HW3/healthcare.csv", skip = 1, header = F, nrows = 1, as.is = T)
df3 = read.csv("/Users/zskurian/Documents/JHU Grad School/DS4BME/HW3/healthcare.csv",  header = F)
colnames(df3)= headers3
tempDF <- df3
tempDF[] <- lapply(df3, as.character)
colnames(df3) <- tempDF[1, ]
df3 <- df3[-1 ,]
tempDF <- NULL
#make the third row the headers
names(df3) <- as.matrix(df3[1, ])
df3 <- df3[-1, ]
df3[] <- lapply(df3, function(x) type.convert(as.character(x)))
#do it again
names(df3) <- as.matrix(df3[1, ])
df3 <- df3[-1, ]
df3[] <- lapply(df3, function(x) type.convert(as.character(x)))
#
#healthtibble <- tibble(df)
longerdf3 <- pivot_longer(df3,cols = -Location, names_to="year",values_to="value")
#Make long format
#remove the beginning and end
#make first row the column headers
#group by Location
longerdf3 = longerdf3[1:1248,]
h = ggplot(longerdf3,aes(x=year,y=value,group=Location,color=Location)) + geom_line()
h = h + theme(axis.text.x = element_text(angle = 90))   
h = h + theme(axis.text.y = element_text(angle = 75))

ggplotly(h)
#df = read.csv("healthcare.csv",  header = F)
#put the long dataframe from problem 5 into a pivot longer
#longerdf10 %>% pivot_longer(df3)
longerdf10 = longerdf3
longerdf11 <- longerdf10 %>% mutate(value=as.double(value))
meanlongerdf11 <- longerdf11 %>% group_by(Location) %>% mutate(Meanspend = mean(value))
meanplot = ggplot(meanlongerdf11,color=Location) + geom_bar(aes(x=Location,y=Meanspend),stat="identity")
meanplot = meanplot + theme(axis.text.x = element_text(angle = 80,hjust=1))   
ggplotly(meanplot)

Question 3

Shiny App - BMI Link to hosted app

Question 4

dat = readSubjectDf("kirb21.txt")
dat = select(dat, -rawid)

df3 <- dat %>% group_by(type, level) %>% summarise_at(vars(volume),mean)

make plot of average

d10 = ggplot(df3,aes(x=type))
d10 = d10 + geom_bar()
d10

d10 = ggplot(df3,color= level) + geom_bar(aes(x= type,y=volume, group = level) ,stat="identity")

Question 5

m = leaflet() %>% 
    addTiles() %>% 
    addMarkers(lat=39.302132, lng=-76.615517, popup="Zina's favorite place")
m